Qiangqiang Gu

collaborators

4 papers

cond-mat.mtrl-sci2025

Deep Learning-Based Quantum Transport Simulations in Two-Dimensional Materials

Jijie Zou, Zhanghao Zhouyin, Qiangqiang Gu +1

Two-dimensional (2D) materials exhibit a wide range of electronic properties that make them promising candidates for next-generation nanoelectronic devices. Accurate prediction of…

cond-mat.mtrl-sci2025

Deep Neural Network for Phonon-Assisted Optical Spectra in Semiconductors

Qiangqiang Gu, Shishir Kumar Pandey, Zhanghao Zhouyin

Ab initio based accurate simulation of phonon-assisted optical spectra of semiconductors at finite temperatures remains a formidable challenge, as it requires large supercells for…

cond-mat.mtrl-sci2025

Learning local equivariant representations for quantum operators

Zhanghao Zhouyin, Zixi Gan, MingKang Liu +3

Predicting quantum operator matrices such as Hamiltonian, overlap, and density matrices in the density functional theory (DFT) framework is crucial for material science. Current me…

cond-mat.mtrl-sci2024

Deep learning tight-binding approach for large-scale electronic simulations at finite temperatures with $ab$ $ini t i o$ accuracy

Qiangqiang Gu, Zhanghao Zhouyin, Shishir Kumar Pandey +3

Simulating electronic behavior in materials and devices with realistic large system sizes remains a formidable task within the $ab$ $ini t i o$ framework due to its computational inte…

Deep Learning-Based Quantum Transport Simulations in Two-Dimensional Materials

Deep Neural Network for Phonon-Assisted Optical Spectra in Semiconductors

Learning local equivariant representations for quantum operators

Deep learning tight-binding approach for large-scale electronic simulations at finite temperatures with ab initio accuracy

Deep learning tight-binding approach for large-scale electronic simulations at finite temperatures with $ab$ $ini t i o$ accuracy